Oxylipin metabolism is controlled by mitochondrial β-oxidation during bacterial inflammation

Oxylipins are potent biological mediators requiring strict control, but how they are removed en masse during infection and inflammation is unknown. Here we show that lipopolysaccharide (LPS) dynamically enhances oxylipin removal via mitochondrial β-oxidation. Specifically, genetic or pharmacological targeting of carnitine palmitoyl transferase 1 (CPT1), a mitochondrial importer of fatty acids, reveal that many oxylipins are removed by this protein during inflammation in vitro and in vivo. Using stable isotope-tracing lipidomics, we find secretion-reuptake recycling for 12-HETE and its intermediate metabolites. Meanwhile, oxylipin β-oxidation is uncoupled from oxidative phosphorylation, thus not contributing to energy generation. Testing for genetic control checkpoints, transcriptional interrogation of human neonatal sepsis finds upregulation of many genes involved in mitochondrial removal of long-chain fatty acyls, such as ACSL1,3,4, ACADVL, CPT1B, CPT2 and HADHB. Also, ACSL1/Acsl1 upregulation is consistently observed following the treatment of human/murine macrophages with LPS and IFN-γ. Last, dampening oxylipin levels by β-oxidation is suggested to impact on their regulation of leukocyte functions. In summary, we propose mitochondrial β-oxidation as a regulatory metabolic checkpoint for oxylipins during inflammation

Algorithm of calculation of standard radio frequency deviation from its nominal value

W artykule przedstawiono algorytm obliczania wskaźników odchylenia radiowej częstotliwości wzorcowej WRC od wartości nominalnej. Algorytm ten oparty jest o metodę Data Mining, w której zastosowano metody grupowania, analizy szeregów czasowych i regresji liniowej.Time and Frequency Laboratory of Central Office of Measures performs measurements of phase time (Fig. 1) of standard radio frequency WRC 225 kHz with reference to 1 Hz pulse signal taken from the national time and frequency standard. Results of these measurements are recorded on a paper tape with analogue data recorder. The indicators characterizing standard radio frequency deviation from its nominal value are calculated on the basis of appropriate data taken from the record diagram and the relationships from (1) to (8). Putting results of phase time measurements into computer memory requires application of a special algorithm, enabling to calculate indicators of WRC frequency deviation from its nominal value. This algorithm is presented in this paper and is based on Data Mining method, employing clusterization, time series analysis and regression line methods